ABOUT ADVANCE MATLAB

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.


Why MATLAB:


MATLAB is used for rapid prototyping and is used in both industries as well as universities. It has a wide range of functions to make coding easier irrespective of the application. Codes are concise and the plotting tools helps to visualize data in an effective manner. The documentation that is available as a part of the software helps in getting things done quickly.


Who Should Do:


B.tech, M.tech, PHD Researchers and other Professional Researchers can join Advance MATLAB course.

Course Highlights

  • Introduction to MATLAB
    Introduction to MATLAB environment
    Command window, workspace, command history
    Basic commands
    Creating variables in MATLAB
    Writing script files
    Logical variables and operators
    Flow control
    Loop operators
    Writing functions
    Input/output arguments
    Function within function
    Plotting
    2D plots
    Figures and subplots
    3D plots
    Mesh and surf plot
    Matrix operations
    Creating matrix, addition, subtraction and multiplication operation
    Creating , accessing elements and manipulating of different types of data
    String operation
    File Input-Output
    Matlab files
    Text files
    Binary files
    Mixed Text- binary files
    Communication with external world
    Serial Port
    Audio Port
    Video Input
    Image processing
    Types of images
    Image arithmetic
    Coordinate systems
    Displaying images
    Basic image related functions
    Reading writing image data
    Region based processing
    Conversion to different color spaces
    Introduction to Simulink
    Simulation of mathematical models
    Solving ordinary differential equations using Simulink blocks
    GUI development
    Introduction to GUI in Matlab
    Creating GUI and making simple calculator
    Creating a GUI for capturing image
    CONTROL SYSTEM TOOLBOX
    MODULE 2
    Creating linear models.
    Data extraction.
    Conversions.
    System interconnections.
    Discussion on state space representation
    System gain and dynamics.
    Frequency-domain analysis.
    Classical design, State Space Model
    Transfer function representation, System response
    Designing of compensator
    Use of SISO design
    FUZZY LOGIC TOOLBOX
    MODULE 3
    Basic introduction to fuzzy logic
    Fuzzy Versus Non-fuzzy Logic
    Foundations of Fuzzy Logic
    Building a fuzzy Inference system
    Modeling using fuzzy logic
    Working from the Command Line
    Simulating and Deploying Fuzzy Inference Systems
    Image Processing Toolbox
    MODULE 4
    Types of images
    Image arithmetic
    Coordinate systems
    Displaying images
    Spatial Transformation
    Reading writing image datae
    Transforms
    Region based processing
    Conversion to different color spaces
    Neighborhood and block operations
    SIMPOWER SYSTEM Toolbox
    MODULE 5
    features
    Modeling Electrical Power System
    Creating Custom Components
    Simulating Models
    Analyzing Models
    Deploying Models
    NEURAL NETWORK TOOLBOX
    MODULE 6
    Network Objects, Data, and Training Styles
    Multilayer Networks and Backpropagation Training
    Control Systems
    Radial Basis Networks
    Self-Organizing and Learning
    Vector Quantization Nets
    Adaptive Filters and Adaptive Training
    COMMUNICATION TOOLBOX
    MODULE 7
    Modeling using Communications System Toolbox
    Analyzing the bit error rate (BER) of a communication system
    Adding channel impairments
    Designing receiver algorithms
    OPTIMIZATION TOOLBOX
    MODULE 8
    Running optimization problems in MATLAB
    Specifying objective functions
    Specifying constraints
    Choosing solvers and algorithms
    Evaluating results and improving performance
    Using global optimization methods
    LIST OF PROJECTS WITH PROJECT SYNOPSIS:
    MODULE 9: PROJECT WORK
    Real Time Object Recognition
    QAM Modulation and Demodulation Technique Implementation
    Noise Reduction in Signals using Adaptive Filters
    Motion Detection using Video Processing
    Multilevel Inverter Design using Multi Carrier Technique
    Induction Motor Control Design in Simulink
    Wireless Data Transmission using Zigbee
    Universal Wireless Motor Controller using Matlab
    Matlab Controlled Wireless Robot


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